Combining survey and geological means to measure illegal mining behavior

2020 ◽  
Vol 2 (1) ◽  
pp. 30-35
Author(s):  
Fang Jianhua
Keyword(s):  
Illegal Mining

scholarly journals The outbreak of illegal gold mining in the Brazilian Amazon boosts deforestation

2021 ◽  
Vol 21 (2) ◽  
Author(s):  
Juliana Siqueira-Gay ◽  
Luis E. Sánchez
Keyword(s):  
Gold Mining ◽  
Brazilian Amazon ◽  
Small Scale ◽  
Political Pressure ◽  
Deforestation Rate ◽  
Mining Areas ◽  
Mineral Supply ◽  
Regional Policies ◽  
Illegal Mining ◽  
Conservation Of Biodiversity

AbstractIncreased prices and political pressure are boosting illegal gold mining in the Brazilian Amazon, threatening forests, indigenous people, and conservation of biodiversity in protected areas. The rate of illegal mining deforestation increased more than 90% from 2017 to 2020, reaching 101.7 km2 annually in 2020 compared to 52.9 km2 annually in 2017. In that period, illegal mining deforestation rate grew more than the rate of clearing within mining leases. While formal mining is required to comply with environmental regulations, most small-scale or artisanal mining and especially illegal mining areas are abandoned after reserves are exhausted, without proper rehabilitation. Deforestation due to illegal mining is likely to increase in the next years, calling for coordination between local and regional policies as well as for strengthening and expanding international mechanisms to increase traceability of mineral supply chains with certification schemes to help to curb illegal mining.

scholarly journals Legacies of a nationwide crackdown in Zimbabwe:Operation Chikorokoza Chaperain gold mining communities

2014 ◽  
Vol 52 (4) ◽  
pp. 541-570 ◽  
Author(s):  
Samuel J. Spiegel
Keyword(s):  
Gold Mining ◽  
Physical Violence ◽  
Power Dynamics ◽  
Mining Sector ◽  
Economic Interests ◽  
Mining Communities ◽  
Diamond Mining ◽  
Illegal Mining ◽  
Artisanal Miners ◽  
Mining Regions

ABSTRACTAlthough conflict in Zimbabwe's diamond mining sector has recently received much international scrutiny, very little research has examined conflict in Zimbabwe's gold mining sector. This article analyses how a nationwide crackdown calledOperation Chikorokoza Chapera(‘No More Illegal Mining’) affected – and ‘disciplined’ – livelihoods in profound ways in both licensed and unlicensed gold mining regions. Drawing on interviews conducted between 2006 and 2013 with artisanal miners in the Insiza, Umzingwani and Kadoma areas as well as miners who crossed the border to Mozambique, the study reveals how a highly politicised crackdown led to uneven consequences. The analysis highlights both structural and physical violence, with more than 25,000 miners and traders arrested between 2006 and 2009 and more than 9,000 still imprisoned in 2013. Situating the crackdown within evolving political and economic interests, the study contributes to an understanding of how simplified discourses on ‘eradicating illegal mining’ mislead and mask power dynamics, while policing activities transform patterns of resource control. The study also emphasises that conceptualisations of the crackdown's legacy should carefully consider the agency of artisanal miners' associations, which, in some cases, have been actively seeking to resist coercive policies and rebuild livelihoods in the aftermath ofOperation Chikorokoza Chapera.

Challenges with eradicating illegal mining in Ghana: A perspective from the grassroots

2008 ◽  
Vol 33 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Sadia Mohammed Banchirigah
Keyword(s):  
Illegal Mining

Use of SAR interferometry for monitoring illegal mining activities: A case study at Xishimen Iron Ore Mine

2011 ◽  
Vol 21 (6) ◽  
pp. 781-786 ◽  
Author(s):  
Maowei Ji ◽  
Xiaojing Li ◽  
Shunchuan Wu ◽  
Yongtao Gao ◽  
Linlin Ge
Keyword(s):  
Iron Ore ◽  
Sar Interferometry ◽  
Mining Activities ◽  
Iron Ore Mine ◽  
Illegal Mining

scholarly journals Automated Sensing System for Real-Time Recognition of Trucks in River Dredging Areas Using Computer Vision and Convolutional Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 555
Author(s):  
Jui-Sheng Chou ◽  
Chia-Hsuan Liu
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Character Recognition ◽  
Initial Period ◽  
Control Point ◽  
Recognition Rate ◽  
Classification Model ◽  
License Plate ◽  
Construction Site ◽  
Illegal Mining

Sand theft or illegal mining in river dredging areas has been a problem in recent decades. For this reason, increasing the use of artificial intelligence in dredging areas, building automated monitoring systems, and reducing human involvement can effectively deter crime and lighten the workload of security guards. In this investigation, a smart dredging construction site system was developed using automated techniques that were arranged to be suitable to various areas. The aim in the initial period of the smart dredging construction was to automate the audit work at the control point, which manages trucks in river dredging areas. Images of dump trucks entering the control point were captured using monitoring equipment in the construction area. The obtained images and the deep learning technique, YOLOv3, were used to detect the positions of the vehicle license plates. Framed images of the vehicle license plates were captured and were used as input in an image classification model, C-CNN-L3, to identify the number of characters on the license plate. Based on the classification results, the images of the vehicle license plates were transmitted to a text recognition model, R-CNN-L3, that corresponded to the characters of the license plate. Finally, the models of each stage were integrated into a real-time truck license plate recognition (TLPR) system; the single character recognition rate was 97.59%, the overall recognition rate was 93.73%, and the speed was 0.3271 s/image. The TLPR system reduces the labor force and time spent to identify the license plates, effectively reducing the probability of crime and increasing the transparency, automation, and efficiency of the frontline personnel’s work. The TLPR is the first step toward an automated operation to manage trucks at the control point. The subsequent and ongoing development of system functions can advance dredging operations toward the goal of being a smart construction site. By intending to facilitate an intelligent and highly efficient management system of dredging-related departments by providing a vehicle LPR system, this paper forms a contribution to the current body of knowledge in the sense that it presents an objective approach for the TLPR system.

Effect of small-scale illegal mining on surface water and sediment quality in Ghana

2021 ◽  
pp. 1-26
Author(s):  
Humphrey Ferdinand Darko ◽  
Anthony Yaw Karikari ◽  
Anthony Appiah Duah ◽  
Bismark Awinbire Akurugu ◽  
Victor Mante ◽  
...  
Keyword(s):  
Surface Water ◽  
Sediment Quality ◽  
Small Scale ◽  
Illegal Mining ◽  
Water And Sediment ◽  
Water And Sediment Quality

scholarly journals A call to halt destructive, illegal mining in Zimbabwe

2017 ◽  
Vol 113 (11/12) ◽  
Author(s):  
Mwazvita T.B. Dalu ◽  
Ryan J. Wasserman ◽  
Tatenda Dalu
Keyword(s):  
Illegal Mining

scholarly journals History, Current Situation and Challenges of Gold Mining in Ecuador’s Litoral Region

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1220
Author(s):  
Carlos Mestanza-Ramón ◽  
Selene Paz-Mena ◽  
Carlos López-Paredes ◽  
Mirian Jimenez-Gutierrez ◽  
Greys Herrera-Morales ◽  
...  
Keyword(s):  
Drinking Water ◽  
Environmental Impacts ◽  
Gold Mining ◽  
Grey Literature ◽  
Terrestrial Ecosystems ◽  
Current Situation ◽  
Socioeconomic Impact ◽  
Mining Sector ◽  
Illegal Mining ◽  
Precautionary Measures

Gold mining in Ecuador has been present in the country since Inca times; over the years interest in the mineral has increased, leading to the creation of legislation to control the mining sector in a safe manner. The Litoral region consists of seven provinces, six of which have registered gold concessions; the most affected provinces are El Oro and Esmeraldas. The objective of this study was to analyze the historical and current situation of artisanal and industrial gold mining in the Litoral region of Ecuador. Different methodologies were used for the elaboration of this study, including bibliographic review, grey literature, field interviews and a validation of expert judgment. The main results indicate that El Oro and Esmeraldas are essentially the most conflictive areas in the region, as they have sometimes had to establish precautionary measures due to the risks caused by illegal mining. In addition, in both areas there is a great socioeconomic impact ranging from lack of opportunities, forgetfulness, migration, emigration, and violation of rights, among others. With respect to environmental impacts, the study highlights the contamination of water sources (which leads to a lack of drinking water for people), and damage to aquatic and terrestrial ecosystems. Finally, the study concludes that the authorities should control the mining sector more by implementing more laws and carrying out inspections to put an end to illegal gold mining, in order to improve the situation in the areas.

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